The Sound that Data Makes

It is common these days to read stories about the sound of black holes, deep space or the abyss. But what if you could turn your data into music? There are a few reasons one might want to do this. First, it adds extra dimensions, in top of those displayed in a scatter plot or a video of your data. Each observation in the sound track may have its own frequency, duration, and volume. That’s three more dimensions. With stereo sound, that’s six dimensions. Add sound texture, and the possibilities are limitless.

Then, sound may allow the human brain to identify new patterns in your data set, not noticeable in scatterplots and other visualizations. This is similar to scatterplots allowing you to see patterns (say clusters) that tabular data is unable to render. Or to data videos, allowing you to see patterns that static visualizations are unable to render. Also, people with vision problems may find sounds more useful than images, to interpret data.

Finally, another purpose of this article is to introduce you to sound processing in Python, and to teach you how to generate sound and music. This basic introduction features some of the fundamental elements. Hopefully, enough to get you started if you are interested to further explore this topic.

Read the full article, listen to data music, and get the Python code, here.